def d3d(tmpdir, dic):
#initialize a model
rpath = str(tmpdir) + '/'
dic.update({'rpath': rpath}) # use tmpdir for running the model
b = pyPoseidon.model(**dic)
try:
b.execute()
a = pyPoseidon.read_model(rpath + 'd3d_model.json') # read model
a.execute()
return True
except:
return False
def schism(tmpdir, case):
#initialize a model
dic = {
'solver': 'schism',
'geometry': case,
'manning': .12,
'windrot': 0.00001,
'tag': 'test',
'start_date': '2017-10-1 0:0:0',
'time_frame': '12H',
'meteo_source': [DATA_DIR / 'erai.grib'], #meteo file
'meteo_engine': 'cfgrib',
'dem_source': DEM_FILE,
'ncores': NCORES, #number of cores
'update': ['all'], #update only meteo, keep dem
'parameters': {
'dt': 400,
'rnday': 0.3,
'nhot': 0,
'ihot': 0,
'nspool': 9,
'ihfskip': 36,
'nhot_write': 108
}
}
rpath = str(tmpdir) + '/'
dic.update({'rpath': rpath}) # use tmpdir for running the model
b = pyPoseidon.model(**dic)
try:
b.execute()
b.results()
return True
except:
return False
def __init__(self,**kwargs):
for attr, value in kwargs.iteritems():
setattr(self, attr, value)
logging.basicConfig(filename=self.path+self.case+'.log',level=logging.INFO)
parent = kwargs.get('parent', '.')
# load model
with open(parent+'info.pkl', 'r') as f:
info=pickle.load(f)
info['minlon'] = kwargs.get('minlon', None)
info['maxlon'] = kwargs.get('maxlon', None)
info['minlat'] = kwargs.get('minlat', None)
info['maxlat'] = kwargs.get('maxlat', None)
info['rpath'] = kwargs.get('rpath', info['rpath']+'./nested/')
rpath = info['rpath'] #save for later
info['resolution'] = kwargs.get('resolution', None)
info['atm'] = False
#create new case
nest = model(**info)
nest.set() #setup nested run
nest.output() #output to run folder
check=[os.path.exists(parent+f) for f in ['u.amu','v.amv','p.amp']]
if np.any(check)==False :
nest.force()
nest.uvp() #write u,v,p files
else: #link u,v,p
for filename in ['u.amu','v.amv','p.amp']:
os.symlink(parent+filename,rpath+filename)
# modify mdf file
inp, order = mdf.read(rpath+nest.impl.tag+'.mdf')
# adjust variables
#create the ini file
if 'Filic' not in order: order.append('Filic')
inp['Filic']=nest.impl.tag + '.ini'
pdata = data([parent])
s1 = pdata.get_data('S1',step=1)
u1 = pdata.get_data('U1',step=1)
v1 = pdata.get_data('V1',step=1)
xz=pdata.get_data('XZ')
yz=pdata.get_data('YZ')
orig = pyresample.geometry.SwathDefinition(lons=xz,lats=yz) # original points
targ = pyresample.geometry.SwathDefinition(lons=nest.impl.grid.x,lats=nest.impl.grid.y) # target grid
s_ini = pyresample.kd_tree.resample_nearest(orig,s1,targ,radius_of_influence=100000,fill_value=0)
u_ini = pyresample.kd_tree.resample_nearest(orig,u1,targ,radius_of_influence=100000,fill_value=0)
v_ini = pyresample.kd_tree.resample_nearest(orig,v1,targ,radius_of_influence=100000,fill_value=0)
# Write .ini file
with open(rpath+nest.impl.tag+'.ini', 'w') as f:
np.savetxt(f,s_ini)
np.savetxt(f,u_ini)
np.savetxt(f,v_ini)
#create the bc file
if 'Filbnd' not in order: order.append('Filbnd')
if 'Filana' not in order: order.append('Filana')
inp['Filbnd']=nest.impl.tag+'.bnd'
inp['Filana']=nest.impl.tag+'.bca'
# bca =
inp['Restid']='##' #no restart file
# update mdf
mdf.write(inp, rpath+nest.impl.tag+'.mdf',selection=order)
# run case
sys.stdout.write('executing\n')
sys.stdout.flush()
os.chdir(rpath)
#subprocess.call(rpath+'run_flow2d3d.sh',shell=True)
nest.run()
nest.save()
logging.info('nesting run done for date :'+datetime.datetime.strftime(date,'%Y%m%d.%H'))
# def get_ini():
# def get_bca():
def d3d(tmpdir,dic):
#initialize a model
rpath = str(tmpdir)
dic.update({'rpath':rpath + '/20181001.00/'}) # use tmpdir for running the model
b = pyPoseidon.model(**dic)
b.execute()
# Cast
#read the info from the first run
with open(rpath+'/20181001.00/d3d_model.json', 'rb') as f:
info = pd.read_json(f,lines=True).T
info[info.isnull().values] = None
info = info.to_dict()[0]
info.update({'path':rpath}) # The path of the project
#creating a time sequence of the runs
start_date = pd.to_datetime('2018-10-1 0:0:0')
end_date = pd.to_datetime('2018-10-1 12:0:0')
date_list = pd.date_range(start_date,end_date, freq='12H')
#append to dic
info.update({'start_date':start_date,'end_date':end_date, 'dates' : date_list})
#creating a sequence of folder to store the runs. In this case we name them after the date attribute.
#NOTE that the first folder is the fisrt run already perfomed!!
folders = [datetime.datetime.strftime(x, '%Y%m%d.%H') for x in date_list]
info.update({'folders':folders})
#set meteo files
meteo = []
for date in date_list:
end_date= pd.to_datetime(date) + pd.to_timedelta(info['time_frame'])
end_date = end_date.strftime(format='%Y-%m-%d %H:%M:%S')
dr = pd.date_range(date, end_date, freq='12H')
dur = [(DATA_DIR / ('uvp_' + datetime.datetime.strftime(x, '%Y%m%d%H') + '.grib')).as_posix() for x in dr]
meteo.append(dur)
info.update({'meteo_source':meteo})
print(meteo)
info.update({'time_frame' : len(folders)*[info['time_frame']]})
h = cast.cast(**info) # initialize
h.run()
# combine output
folders = [info['path']+'/'+f for f in info['folders']]
res = data.data(folders=folders,solver='d3d')
# check single run
case2.update({'rpath':rpath + '/combined/'})
a = pyPoseidon.model(**case2)
a.execute()
out = data.data(**case2)
test = True
for var in out.Dataset.data_vars:
if not out.Dataset[var].equals(res.Dataset[var]):
if np.abs(out.Dataset[var].values-res.Dataset[var].values).max() > 1.e-6 : test = False
return test
def d3d(tmpdir):
#initialize a model
rpath = str(tmpdir) + '/d3d/'
case.update({'rpath':
rpath + '/20181001.00/'}) # use tmpdir for running the model
b = pyPoseidon.model(**case)
b.execute()
#creating a time sequence of the runs
start_date = pd.to_datetime('2018-10-1 0:0:0')
end_date = pd.to_datetime('2018-10-2 0:0:0')
date_list = pd.date_range(start_date, end_date, freq='12H')
#creating a sequence of folder to store the runs. In this case we name them after the date attribute.
#NOTE that the first folder is the fisrt run already perfomed!!
rpaths = [
rpath + datetime.datetime.strftime(x, '%Y%m%d.%H') + '/'
for x in date_list
]
#set meteo files
meteo = []
for date in date_list:
end_date = pd.to_datetime(date) + pd.to_timedelta('12H')
end_date = end_date.strftime(format='%Y-%m-%d %H:%M:%S')
dr = pd.date_range(date, end_date, freq='12H')
names = [
'uvp_' + datetime.datetime.strftime(x, '%Y%m%d%H') + '.grib'
for x in dr
]
dur = [(DATA_DIR / name).as_posix() for name in names]
meteo.append(dur)
#set cast
for l in range(len(rpaths) - 1):
h = cast.cast(solver='d3d',
model=b,
ppath=rpaths[l],
cpath=rpaths[l + 1],
meteo=meteo[l + 1],
date=date_list[l + 1])
h.set(execute=True) # execute
# Run check case - Total duration
check.update({'rpath':
rpath + 'check/'}) # use tmpdir for running the model
c = pyPoseidon.model(**check)
c.execute()
# COMPARE
output = data.data(folders=rpaths, solver='d3d')
total = data.data(folders=[rpath + 'check/'], solver='d3d')
test = True
rb = []
for var in total.Dataset.data_vars:
if not total.Dataset[var].equals(output.Dataset[var]):
rb.append(var)
if np.abs(total.Dataset[var].values -
output.Dataset[var].values).max() > 1.e-6:
test = False
print(rb)
return test
def schism(tmpdir):
#initialize a model
rpath = str(tmpdir)+'/schism/'
case.update({'rpath':rpath+'20181001.00/'}) # use tmpdir for running the model
b = pyPoseidon.model(**case)
b.execute()
#creating a time sequence of the runs
start_date = pd.to_datetime('2018-10-1 0:0:0')
end_date = pd.to_datetime('2018-10-2 0:0:0')
date_list = pd.date_range(start_date,end_date, freq='12H')
#creating a sequence of folder to store the runs. In this case we name them after the date attribute.
#NOTE that the first folder is the fisrt run already perfomed!!
rpaths = [rpath + datetime.datetime.strftime(x, '%Y%m%d.%H') +'/' for x in date_list]
#creating a sequence of folder from which we read the meteo.
meteo = []
for date in date_list:
prev_date= pd.to_datetime(date) - pd.to_timedelta('12H')
prev_date = prev_date.strftime(format='%Y-%m-%d %H:%M:%S')
dr = pd.date_range(prev_date, date, freq='12H')
names = ['uvp_'+ datetime.datetime.strftime(x, '%Y%m%d%H') + '.grib' for x in dr]
dur = [ (DATA_DIR / name).as_posix() for name in names ]
meteo.append(dur)
#set cast
for l in range(len(rpaths)-1):
h = cast.cast(solver='schism',model=b,ppath=rpaths[l],cpath=rpaths[l+1],meteo=meteo[l+1], date=date_list[l+1])
h.set(execute=True) # execute
# Run check case - Total duration
check.update({'rpath':rpath+'check/'}) # use tmpdir for running the model
# Combine meteo appropriately
m1 = pm.meteo(meteo_source=METEO_FILES_2[0],meteo_engine='cfgrib')
m2 = pm.meteo(meteo_source=METEO_FILES_2[1],meteo_engine='cfgrib')
m3 = pm.meteo(meteo_source=METEO_FILES_2[2],meteo_engine='cfgrib')
m4 = pm.meteo(meteo_source=METEO_FILES_2[3],meteo_engine='cfgrib')
# extract correct chunk
w1 = m1.Dataset.isel(time=slice(0,13))
w2 = m2.Dataset.isel(time=slice(1,13)) # note that we keep the 12 hour from the previous file
w3 = m3.Dataset.isel(time=slice(1,13))
w4 = m4.Dataset.isel(time=slice(1,13))
#combine
meteo = xr.combine_by_coords([w1,w2,w3,w4],combine_attrs='override')
#saving
check.update({'meteo_source' : meteo})
c = pyPoseidon.model(**check)
c.execute()
# COMPARE
output = data.data(folders=rpaths,solver='schism')
total = data.data(folders=[rpath+'check/'],solver='schism')
r = output.Dataset.isel(time=slice(0,36))
rb = []
for var in total.Dataset.data_vars:
if not total.Dataset[var].equals(r[var]):
rb.append(var)
print(rb)
# flag = True TODO
# for var in rb:
# flag = False
# mdif = np.abs(total.results.Dataset[var].values - output.results.Dataset[var].values).max()
# if mdif < 1.e-14 :
# flag = True
# print(mdif)
if (rb == ['zcor']) or rb==[]:
return True
else:
return False
def schism(tmpdir):
#initialize a model
rpath = str(tmpdir) + '/schism/'
case.update({'rpath':
rpath + '20181001.00/'}) # use tmpdir for running the model
b = pyPoseidon.model(**case)
b.execute()
# run the cast
with open(rpath + '20181001.00/schism_model.json', 'rb') as f:
info = pd.read_json(f, lines=True).T
info[info.isnull().values] = None
info = info.to_dict()[0]
info.update({'path': rpath})
#creating a time sequence of the runs
start_date = pd.to_datetime('2018-10-1 0:0:0')
end_date = pd.to_datetime('2018-10-2 0:0:0')
date_list = pd.date_range(start_date, end_date, freq='12H')
#append to dic
info.update({
'start_date': start_date,
'end_date': end_date,
'dates': date_list
})
#creating a sequence of folder to store the runs. In this case we name them after the date attribute.
#NOTE that the first folder is the fisrt run already perfomed!!
folders = [datetime.datetime.strftime(x, '%Y%m%d.%H') for x in date_list]
info.update({'folders': folders})
#creating a sequence of folder from which we read the meteo.
meteo = []
for date in date_list:
end_date = pd.to_datetime(date) + pd.to_timedelta(info['time_frame'])
end_date = end_date.strftime(format='%Y-%m-%d %H:%M:%S')
dr = pd.date_range(date, end_date, freq='12H')
names = [
'uvp_' + datetime.datetime.strftime(x, '%Y%m%d%H') + '.grib'
for x in dr
]
dur = [(DATA_DIR / name).as_posix() for name in names]
meteo.append(dur)
info.update({'meteo_source': meteo})
info['time_frame'] = len(folders) * [info['time_frame']]
#set cast
h = cast.cast(**info) # initialize
h.run()
# Run check case - Total duration
check.update({'rpath':
rpath + 'check/'}) # use tmpdir for running the model
c = pyPoseidon.model(**check)
c.execute()
# COMPARE
folders = [info['path'] + f for f in info['folders']]
output = data.data(folders=folders, solver='schism')
total = data.data(folders=[rpath + 'check/'], solver='schism')
rb = []
for var in total.Dataset.data_vars:
if not total.Dataset[var].equals(output.Dataset[var]):
rb.append(var)
print(rb)
# flag = True TODO
# for var in rb:
# flag = False
# mdif = np.abs(total.results.Dataset[var].values - output.results.Dataset[var].values).max()
# if mdif < 1.e-14 :
# flag = True
# print(mdif)
if (rb == ['zcor']) or rb == []:
return True
else:
return False
def schism(tmpdir):
#initialize a model
rpath = str(tmpdir) + '/schism/'
case.update({'rpath':
rpath + '20181001.00/'}) # use tmpdir for running the model
#creating a time sequence of the runs
start_date = pd.to_datetime('2018-10-1 0:0:0')
end_date = pd.to_datetime('2018-10-2 0:0:0')
date_list = pd.date_range(start_date, end_date, freq='12H')
m0 = pm.meteo(meteo_source=METEO_FILES_1, engine='cfgrib')
case.update({'meteo_source': m0.Dataset})
b = pyPoseidon.model(**case)
b.execute()
# run the cast
with open(rpath + '20181001.00/schism_model.json', 'rb') as f:
info = pd.read_json(f, lines=True).T
info[info.isnull().values] = None
info = info.to_dict()[0]
info.update({'path': rpath})
#append to dic
info.update({
'start_date': start_date,
'end_date': end_date,
'dates': date_list
})
#creating a sequence of folder to store the runs. In this case we name them after the date attribute.
#NOTE that the first folder is the fisrt run already perfomed!!
folders = [datetime.datetime.strftime(x, '%Y%m%d.%H') for x in date_list]
info.update({'folders': folders})
#creating a sequence of folder from which we read the meteo.
meteo = [m0.Dataset]
for date in date_list[1:]:
end_date = pd.to_datetime(date) + pd.to_timedelta(info['time_frame'])
end_date = end_date.strftime(format='%Y-%m-%d %H:%M:%S')
dr = [date - pd.to_timedelta('12H'), date]
names = [
'uvp_' + datetime.datetime.strftime(x, '%Y%m%d%H') + '.grib'
for x in dr
]
dur = [(DATA_DIR / name).as_posix() for name in names]
m1 = pm.meteo(meteo_source=dur[0], engine='cfgrib')
m2 = pm.meteo(meteo_source=dur[1], engine='cfgrib')
w1 = m1.Dataset.isel(time=slice(12, 13))
w2 = m2.Dataset.isel(time=slice(
1, None)) # note that we keep the 12 hour from the previous file
mf = xr.combine_by_coords([w1, w2])
meteo.append(mf)
info.update({'meteo_source': meteo})
info['time_frame'] = len(folders) * [info['time_frame']]
#set cast
h = cast.cast(**info) # initialize
h.run()
# Run check case - Total duration
check.update({'rpath':
rpath + 'check/'}) # use tmpdir for running the model
# Combine meteo appropriately
m1 = pm.meteo(meteo_source=METEO_FILES_2[0], engine='cfgrib')
m2 = pm.meteo(meteo_source=METEO_FILES_2[1], engine='cfgrib')
m3 = pm.meteo(meteo_source=METEO_FILES_2[2], engine='cfgrib')
m4 = pm.meteo(meteo_source=METEO_FILES_2[3], engine='cfgrib')
# extract correct chunk
w1 = m1.Dataset.isel(time=slice(0, 13))
w2 = m2.Dataset.isel(time=slice(
1, 13)) # note that we keep the 12 hour from the previous file
w3 = m3.Dataset.isel(time=slice(1, 13))
w4 = m4.Dataset.isel(time=slice(1, 13))
#combine
meteo = xr.combine_by_coords([w1, w2, w3, w4])
#saving
check.update({'meteo_source': meteo})
c = pyPoseidon.model(**check)
c.execute()
# COMPARE
folders = [info['path'] + f for f in info['folders']]
output = data.data(folders=folders, solver='schism')
total = data.data(folders=[rpath + 'check/'], solver='schism')
r = output.Dataset.isel(time=slice(0, 36))
rb = []
for var in total.Dataset.data_vars:
if not total.Dataset[var].equals(r[var]):
rb.append(var)
print(rb)
# flag = True TODO
# for var in rb:
# flag = False
# mdif = np.abs(total.results.Dataset[var].values - output.results.Dataset[var].values).max()
# if mdif < 1.e-14 :
# flag = True
# print(mdif)
if (rb == ['zcor']) or rb == []:
return True
else:
return False
